Average Error: 64.0 → 64.0
Time: 12.0s
Precision: 64
\[1.9 \le t \le 2.1\]
\[1.7 \cdot 10^{+308} \cdot t - 1.7 \cdot 10^{+308}\]
↓
\[1.7 \cdot 10^{+308} \cdot t - 1.7 \cdot 10^{+308}\]
1.7 \cdot 10^{+308} \cdot t - 1.7 \cdot 10^{+308}
↓
1.7 \cdot 10^{+308} \cdot t - 1.7 \cdot 10^{+308}
double f(double t) {
        double r2844144 = 1.7e+308;
        double r2844145 = t;
        double r2844146 = r2844144 * r2844145;
        double r2844147 = r2844146 - r2844144;
        return r2844147;
}
↓
double f(double t) {
        double r2844148 = 1.7e+308;
        double r2844149 = t;
        double r2844150 = r2844148 * r2844149;
        double r2844151 = r2844150 - r2844148;
        return r2844151;
}

Error

Bits error versus t

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Target

Original64.0
Target0
Herbie64.0
\[\mathsf{fma}\left(1.7 \cdot 10^{+308}, t, -1.7 \cdot 10^{+308}\right)\]

Derivation

  1. Initial program 64.0

    \[1.7 \cdot 10^{+308} \cdot t - 1.7 \cdot 10^{+308}\]

  2. Final simplification64.0

    \[\leadsto 1.7 \cdot 10^{+308} \cdot t - 1.7 \cdot 10^{+308}\]

Reproduce

herbie shell --seed 2019165 
(FPCore (t)
  :name "fma_test2"
  :pre (<= 1.9 t 2.1)

  :herbie-target
  (fma 1.7e+308 t (- 1.7e+308))

  (- (* 1.7e+308 t) 1.7e+308))